Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI – Page 1487

“Technological advances in robotics have already produced robots that are indistinguishable from human beings,” they write. “If humanoid robots with the same appearance are mass-produced and become commonplace, we may encounter circumstances in which people or human-like products have faces with the exact same appearance in the future.”

To test peoples’ reactions, the team asked people to look at photos of individuals with the same face (clones), with different faces, and of… See more.

The uncanny valley is the scientific explanation for why we all find clowns or corpses creepy. And just when we thought nothing could be more alarming than clowns, scientists have found an even uncannier way to freak us out.

New research finds that there is something even creepier than the uncanny valley: clones. Scientists now predict that when convincing humanoid robots with identical faces are launched, we are all going to panic.

Continue reading “New Robots May Be Creepier Than The Uncanny Valley” | >

In conversation with my teenage daughter last week, I pointed out a news report which flagged concerns over the use of facial recognition technologies in several school canteens in North Ayrshire, Scotland. Nine schools in the area recently launched this practice as a means to take payment for lunches more quickly and minimize COVID risk, though they’ve since paused rolling out the technology.

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Hundreds of millions of years of evolution have produced a variety of life-forms, each intelligent in its own fashion. Each species has evolved to develop innate skills, learning capacities, and a physical form that ensures survival in its environment.

But despite being inspired by nature and evolution, the field of artificial intelligence has largely focused on creating the elements of intelligence separately and fusing them together after the development process. While this approach has yielded great results, it has also limited the flexibility of AI agents in some of the basic skills found in even the simplest life-forms.

In a new paper published in the scientific journal Nature, AI researchers at Stanford University present a new technique that can help take steps toward overcoming some of these limits. Called “deep evolutionary reinforcement learning,” or DERL, the new technique uses a complex virtual environment and reinforcement learning to create virtual agents that can evolve both in their physical structure and learning capacities. The findings can have important implications for the future of AI and robotics research.

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Elon Musk has announced the upcoming release of Tesla’s Full Self-Driving Beta 10.4 update as Tesla slows down the rollout.

Earlier this week, Tesla started rolling out Full Self-Driving Beta 10.3.

The update came after a false start last weekend when Tesla pushed the update with some problems and ended up reverting back to 10.2.

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Thankfully, there is a growing effort toward AI For Good.

This latest mantra entails ways to try and make sure that the advances in AI are being applied for the overall betterment of mankind. These are assuredly laudable endeavors and reassuringly crucial that the technology underlying AI is aimed and deployed in an appropriate and assuredly positive fashion (for my coverage on the burgeoning realm of AI Ethics, see the link here).

Unfortunately, whether we like it or not, there is the ugly side of the coin too, namely the despicable AI For Bad.

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The final humorous argument I have is if one example is really a robot. Aylett and Vargas describe a “robot” as a humanoid machine that doesn’t manipulate anything. It just provides information at a shopping center. How does that fit into their own definition of a robot? It sounds more like an overgrown tablet computer with wheels. However, that’s a fun argument having nothing to do with the business value of whatever you want to call it.

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This is a review of the third book sent to me recently by MIT Press, and the book is the best of the bunch. “Living With Robots,” by Ruth Aylett and Patricia A. Vargas is a good, non-technical book that discusses a number of issues with robots in human society. This is excellent for both business managers and those more generally interested in both the promise and reality of robots in society.

One exam of the accessibility of the material is in chapter 8 where there’s a discussion on reinforcement learning. There are good theoretical examples and how reinforcement learning has risks in the real world. I really liked the part where the authors discuss blending simulation and real world testing.

Continue reading ““Living With Robots” — An Excellent Non-Technical Overview Of Robotics” | >